The present disclosure relates generally to the fields of natural language understanding (NLU) and artificial intelligence (AI), and more specifically, to a hybrid learning system for NLU.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Cloud computing relates to the sharing of computing resources that are generally accessed via the Internet. In particular, a cloud computing infrastructure allows users, such as individuals and/or enterprises, to access a shared pool of computing resources, such as servers, storage devices, networks, applications, and/or other computing based services. By doing so, users are able to access computing resources on demand that are located at remote locations and these resources may be used to perform a variety computing functions (e.g., storing and/or processing large quantities of computing data). For enterprise and other organization users, cloud computing provides flexibility in accessing cloud computing resources without accruing large up-front costs, such as purchasing expensive network equipment or investing large amounts of time in establishing a private network infrastructure. Instead, by utilizing cloud computing resources, users are able redirect their resources to focus on their enterprise's core functions.
In modern communication networks, examples of cloud computing services a user may utilize include so-called infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS) technologies. IaaS is a model in which providers abstract away the complexity of hardware infrastructure and provide rapid, simplified provisioning of virtual servers and storage, giving enterprises access to computing capacity on demand. In such an approach, however, a user may be left to install and maintain platform components and applications. SaaS is a delivery model that provides software as a service rather than an end product. Instead of utilizing a local network or individual software installations, software is typically licensed on a subscription basis, hosted on a remote machine, and accessed by client customers as needed. For example, users are generally able to access a variety of enterprise and/or information technology (IT)-related software via a web browser. PaaS acts an extension of SaaS that goes beyond providing software services by offering customizability and expandability features to meet a user's needs. For example, PaaS can provide a cloud-based developmental platform for users to develop, modify, and/or customize applications and/or automating enterprise operations without maintaining network infrastructure and/or allocating computing resources normally associated with these functions.
Such a cloud computing service may host a virtual agent, such as a chat agent, that is designed to automatically respond to issues with the client instance based on natural language requests from a user of the client instance. For example, a user may provide a request to a virtual agent for assistance with a password issue, wherein the virtual agent is part of a Natural Language Processing (NLP) or Natural Language Understanding (NLU) system. NLP is a general area of computer science and AI that involves some form of processing of natural language input. Examples of areas addressed by NLP include language translation, speech generation, parse tree extraction, part-of-speech identification, and others. NLU is a sub-area of NLP that specifically focuses on understanding user utterances. Examples of areas addressed by NLU include question-answering (e.g., reading comprehension questions), article summarization, and others. For example, a NLU may use algorithms to reduce human language (e.g., spoken or written) into a set of known symbols for consumption by a downstream virtual agent. NLP is generally used to interpret free text for further analysis. Current approaches to NLP are typically based on deep learning, which is a type of AI that examines and uses patterns in data to improve the understanding of a program.
As such, it is presently recognized that there is a need to improve the ability of virtual agents to apply NLU techniques to properly derive meaning from complex natural language utterances. For example, it may be advantageous to create a virtual agent capable of comprehending complex language and executing contextually relevant requests, which could afford substantial advantages in terms of reduced operational cost and increased responsiveness to client issues. Additionally, it is recognized that it is advantageous for virtual agents to be customizable and adaptable to various communication channels and styles.